Solar energy paper index
Statistical insights on the decorrelation lengths of solar wind parameters at L1 point under varying conditions
One-line summary
A solar energy research paper on Statistical insights on the decorrelation lengths of solar wind parameters at L1 point under varying conditions.
Engineering notes
Engineering notes will be added by the Power for Solar editorial team.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。
Original abstract
Understanding the spatial coherence of solar wind plasma and magnetic field properties is essential for interpreting multi-spacecraft observations and for characterizing the large-scale structure of heliospheric transients. In this study, we quantify the spatial correlation of six key solar wind parameters - interplanetary magnetic field components, bulk flow speed, proton number density, and the alpha-to-proton abundance ratio - using simultaneous measurements from the ACE and Wind spacecraft as a function of their instantaneous separation distance. The analysis is performed separately for intervals of background solar wind, Interplanetary Coronal Mass Ejections (ICMEs), and Stream Interaction Regions (SIRs). The decay of the Pearson correlation coefficient with distance is modeled using an exponential function to infer characteristic de-correlation length scales. We find that the bulk solar wind speed is the most spatially coherent parameter in all regimes, while plasma composition exhibits the weakest coherence. Magnetic field coherence shows strong dependence on solar wind structure: ICMEs display near-unity correlations and the largest magnetic coherence scales, consistent with organized, flux-rope-like configurations, whereas SIRs exhibit reduced coherence - particularly in the north - south magnetic field component - reflecting compressed and turbulent plasma. The background solar wind exhibits intermediate behavior, with large-scale coherence in bulk plasma properties but shorter coherence lengths in magnetic fluctuations. These results provide a quantitative framework for distinguishing solar wind structures based on their spatial coherence properties and have important implications for multi-point solar wind studies and space weather applications.
Links and sources
Need this topic turned into a technical roadmap?
Power for Solar can prepare a custom solar energy literature review, simulation code map, dataset map, and B2B photovoltaic technology assessment.
Request B2B research
Comments